AI agent chat

Empower your applications with an intelligent AI agent capable of dynamic, context-aware conversations and real-time information retrieval. This workflow automates the process of handling incoming chat messages, directing them to an AI agent that leverages OpenAI's advanced language models for generating responses and SerpAPI for searching the web. It connects the "When chat message received" trigger directly to the "AI Agent" node, which then orchestrates interactions with the "OpenAI Chat Model" for conversational intelligence and the "SerpAPI" tool for fetching up-to-date information, all while maintaining conversational history using the "Window Buffer Memory" node. Businesses can use this for enhanced customer support chatbots, interactive product guides, or internal knowledge base assistants, providing instant, accurate answers and reducing the workload on human agents. This significantly saves time and effort by automating complex information retrieval and conversational tasks, allowing your team to focus on more strategic initiatives.

5 nodesmanual trigger122 views0 copiesAI
OpenAI

Workflow JSON

{"meta": {"instanceId": "408f9fb9940c3cb18ffdef0e0150fe342d6e655c3a9fac21f0f644e8bedabcd9"}, "nodes": [{"id": "939bb301-5e12-4d5b-9a56-61a61cca5f0d", "name": "OpenAI Chat Model", "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi", "position": [640, 460], "parameters": {"model": "gpt-4o-mini", "options": {}}, "credentials": {"openAiApi": {"id": "", "name": "[Your openAiApi]"}}, "typeVersion": 1}, {"id": "372777e8-ce90-4dea-befc-ac1b2eb4729f", "name": "Window Buffer Memory", "type": "@n8n/n8n-nodes-langchain.memoryBufferWindow", "position": [780, 460], "parameters": {}, "typeVersion": 1.2}, {"id": "7a8f0ad1-1c00-4043-b3e5-c88521140a1a", "name": "SerpAPI", "type": "@n8n/n8n-nodes-langchain.toolSerpApi", "position": [920, 460], "parameters": {"options": {}}, "credentials": {"serpApi": {"id": "", "name": "[Your serpApi]"}}, "typeVersion": 1}, {"id": "a7624108-e3da-4193-a625-887314216b8b", "name": "When chat message received", "type": "@n8n/n8n-nodes-langchain.chatTrigger", "position": [360, 240], "webhookId": "53c136fe-3e77-4709-a143-fe82746dd8b6", "parameters": {"options": {}}, "typeVersion": 1.1}, {"id": "6b8b7de8-fe3f-43b5-97ce-a52a9e44eb5e", "name": "AI Agent", "type": "@n8n/n8n-nodes-langchain.agent", "position": [680, 240], "parameters": {"options": {}}, "typeVersion": 1.6}], "pinData": {}, "connections": {"SerpAPI": {"ai_tool": [[{"node": "AI Agent", "type": "ai_tool", "index": 0}]]}, "OpenAI Chat Model": {"ai_languageModel": [[{"node": "AI Agent", "type": "ai_languageModel", "index": 0}]]}, "Window Buffer Memory": {"ai_memory": [[{"node": "AI Agent", "type": "ai_memory", "index": 0}]]}, "When chat message received": {"main": [[{"node": "AI Agent", "type": "main", "index": 0}]]}}}

How to Import This Workflow

  1. 1Copy the workflow JSON above using the Copy Workflow JSON button.
  2. 2Open your n8n instance and go to Workflows.
  3. 3Click Import from JSON and paste the copied workflow.

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